Generating a Model Using the Naive Bayes Algorithm

Introduction

This sample demonstrates how a model is generated out of a data set using the Naive Bayes algorithm. The sample uses a data set to generate a model, which is divided into two sets for training and testing.

Prerequisites

Download WSO2 Machine Learner, and start the server. For information on setting up and running WSO2 ML, see Getting Started.

Building the sample

Execute the following command to download the source code of the product: git clone https://github.com/wso2/product-ml.git

Executing the sample

Once the sample is successfully executed, you obtain the following output.

1. Follow the steps below if you already executed a sample before.

   • Execute the following command to remove the databases created: rm -rf repository/database/WSO2ML_DB.*
   • Navigate to <ML_HOME>/bin/ directory using the CLI.
   • Restart the WSO2 ML server by executing the following command: ./wso2server.sh -Dsetup 

2. Navigate to <ML_HOME>/samples/rest-api/naive-bayes/ directory using the CLI.

   <ML_HOME> refers to the downloaded product-ml directory with the source code of the product.

3. Execute the following command to execute the sample: sh model-generation.sh

Output of the sample

If the sample executed successfully, the model will be generated by default in the /tmp/ directory of your machine. For example, the generated file will be in the following format denoting the date and time when it was generated: model.1.2015-03-20_13:29:10

{
"type" : "file",
"location" : "/tmp"
}